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Machine Learning Infrastructure Engineer in Amsterdam

Relay42

Workplace
Onsite
Hours
Full-Time
Internship
No
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Job Description

The Machine Learning Infrastructure Engineer will be working on the infrastructure to run machine learning models in near real-time. This involves building scalable, highly performant data pipelines and architecting the underlying platform. Do you love to design and develop scalable infrastructure? We are looking for colleagues who want to help our clients deliver optimal and personalized marketing outcomes using machine learning.


Requirements

Your role as a Machine Learning Infrastructure Engineer is to be creative in delivering scalable solutions to complex features and setup an infrastructure that handles thousands of predictions per second. Therefore we would love to see you have:

 

  • Experience with Spark, Scala and Python
  • At least one year experience working with a JVM language (Java / Scala)
  • Experience with streaming processing technologies such as Spark Streaming, Kafka or Kinesis
  • A high coding standard and ability to judge implications for performance of processes
  • Nice to have: experience with machine learning

We would like to have a human conversation, again. Hello. How are you?

 

At Relay42 we are here to humanise digital marketing. We make sure marketeers speak to the right person, in the right language, at the right time, in the right place. Why? To fulfil the promise of big data and fix the broken customer journey. Let us introduce ourselves.

Relay42 has grown from a start-up to a champion in data marketing technology in Europe. Our Development team is in the core of our business. The team has a variety of disciplines and decisions are made together as a whole. We work cross country and have multiple nationalities in the Development team. We welcome new ideas and offer the opportunity to explore and develop these further. Together we will conquer and break down the 'walled gardens' in the world of online marketing. Are you ready to connect?

Apply now? Let’s start the conversation!


 

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